Search Results for author:
Found 10 papers, 6 papers with code
Right for the Right Reason: Evidence Extraction for Trustworthy Tabular Reasoning
On the downstream tabular inference task, using only the automatically extracted evidence as the premise, our approach outperforms prior benchmarks.
TempTabQA: Temporal Question Answering for Semi-Structured Tables
Given these results, our dataset has the potential to serve as a challenging benchmark to improve the temporal reasoning capabilities of NLP models.
Anchor-Intermediate Detector: Decoupling and Coupling Bounding Boxes for Accurate Object Detection
The corner-aware head is able to score the corners of each bounding box to facilitate the coupling between corner points.
Pedestrian-Robot Interactions on Autonomous Crowd Navigation: Reactive Control Methods and Evaluation Metrics
Autonomous navigation in highly populated areas remains a challenging task for robots because of the difficulty in guaranteeing safe interactions with pedestrians in unstructured situations.
Automatic Construction of Enterprise Knowledge Base
In this paper, we present an automatic knowledge base construction system from large scale enterprise documents with minimal efforts of human intervention.
MedSelect: Selective Labeling for Medical Image Classification Combining Meta-Learning with Deep Reinforcement Learning
We propose a selective learning method using meta-learning and deep reinforcement learning for medical image interpretation in the setting of limited labeling resources.
MULLS: Versatile LiDAR SLAM via Multi-metric Linear Least Square
The rapid development of autonomous driving and mobile mapping calls for off-the-shelf LiDAR SLAM solutions that are adaptive to LiDARs of different specifications on various complex scenarios.
Cross-Lingual Named Entity Recognition Using Parallel Corpus: A New Approach Using XLM-RoBERTa Alignment
We built an entity alignment model on top of XLM-RoBERTa to project the entities detected on the English part of the parallel data to the target language sentences, whose accuracy surpasses all previous unsupervised models.
Ranked #2 on
Cross-Lingual NER
on CoNLL 2003
Towards Robust Visual Tracking for Unmanned Aerial Vehicle with Tri-Attentional Correlation Filters
Object tracking has been broadly applied in unmanned aerial vehicle (UAV) tasks in recent years.
Optimal Action Extraction for Random Forests and Boosted Trees
To address this problem, we present a novel framework to post-process any ATM classifier to extract an optimal actionable plan that can change a given input to a desired class with a minimum cost.
